Instructions to use TuwaiqAcademy/AISA-AR-FunctionCall-Think with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TuwaiqAcademy/AISA-AR-FunctionCall-Think with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TuwaiqAcademy/AISA-AR-FunctionCall-Think")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TuwaiqAcademy/AISA-AR-FunctionCall-Think")
model = AutoModelForCausalLM.from_pretrained("TuwaiqAcademy/AISA-AR-FunctionCall-Think")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TuwaiqAcademy/AISA-AR-FunctionCall-Think with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TuwaiqAcademy/AISA-AR-FunctionCall-Think"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TuwaiqAcademy/AISA-AR-FunctionCall-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TuwaiqAcademy/AISA-AR-FunctionCall-Think

SGLang

How to use TuwaiqAcademy/AISA-AR-FunctionCall-Think with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "TuwaiqAcademy/AISA-AR-FunctionCall-Think" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TuwaiqAcademy/AISA-AR-FunctionCall-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "TuwaiqAcademy/AISA-AR-FunctionCall-Think" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TuwaiqAcademy/AISA-AR-FunctionCall-Think",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TuwaiqAcademy/AISA-AR-FunctionCall-Think with Docker Model Runner:
```
docker model run hf.co/TuwaiqAcademy/AISA-AR-FunctionCall-Think
```

Omartificial-Intelligence-Space commited on 4 days ago

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@@ -228,8 +228,6 @@ Scored on the AISA-ArabicFC **held-out test set** (1,000 positive + negative exa
 - 🏆 **Shared task page:** https://huggingface.co/spaces/Omartificial-Intelligence-Space/AISA-ArabicFC-Shared-Task
 - 📊 **Leaderboard:** https://huggingface.co/spaces/TuwaiqAcademy/AISA-ArabicFC-SharedTask-Leaderboard
 - 📚 **Dataset (train + dev):** [TuwaiqAcademy/AISA-ArabicFC](https://huggingface.co/datasets/TuwaiqAcademy/AISA-ArabicFC)
-- 🧠 **Reasoning dataset:** [Omartificial-Intelligence-Space/AISA-AR-FunctionCall-Reasoning](https://huggingface.co/datasets/Omartificial-Intelligence-Space/AISA-AR-FunctionCall-Reasoning)
-- 🤝 **Sibling baseline (Track A):** [TuwaiqAcademy/AISA-AR-FunctionCall-FT](https://huggingface.co/TuwaiqAcademy/AISA-AR-FunctionCall-FT)
 ---
@@ -250,5 +248,5 @@ This model is a derivative of **Gemma 3** and is distributed under the **[Gemma
 ## Contact
-Shared-task organizers — **arabicnlp-shared-task-chair@sigarab.org** · Tuwaiq Academy
 ```

 - 🏆 **Shared task page:** https://huggingface.co/spaces/Omartificial-Intelligence-Space/AISA-ArabicFC-Shared-Task
 - 📊 **Leaderboard:** https://huggingface.co/spaces/TuwaiqAcademy/AISA-ArabicFC-SharedTask-Leaderboard
 - 📚 **Dataset (train + dev):** [TuwaiqAcademy/AISA-ArabicFC](https://huggingface.co/datasets/TuwaiqAcademy/AISA-ArabicFC)
 ---
 ## Contact
+Shared-task organizers — **trdc@tuwaiq.edu.sa** · Tuwaiq Academy
 ```